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检索条件"主题词=Recursive least squares algorithm"

共 92 条记录，以下是61-70 订阅

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Variable Forgetting Factor Estimation in Impulsive Noise Environment 22

Variable Forgetting Factor Estimation in Impulsive Noise Env...

引用

22nd Telecommunications Forum Telfor (TELFOR)

作者： Banjac, Z. Kovacevic, B. Kostic-Kovacevic, I. Sch Elect & Comp Engn Appl Studies Belgade Vojvode Stepe 283 Belgrade 11000 Serbia Univ Belgrade Sch Elect Engn Belgrade 11120 Serbia Singidunum Univ Fac Informat & Comp Belgrade 11000 Serbia

ISBN: (纸本)9781479961917

In this paper, a new robust adaptive FIR filter algorithm with variable forgetting factor for time-varying parameters estimation in the presence of impulsive noise is discussed. The proposed algorithm is based on the robust recursive least square and extended prediction error variable forgetting factor adaptation algorithms. The feasibility of the approach is demonstrated in a system identification simulation using a FIR filter application.

关键词： Adaptive filtering recursive least squares algorithm variable forgetting factor extended prediction error time-varying parameters nonstationary environment

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Blind Equalization under Noisy Environment using Bias-compensated RLS method 40

Blind Equalization under Noisy Environment using Bias-compen...

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40th Chinese Control Conference (CCC)

作者： Zhang, Zhen Jia, Lijuan Kanae, Shunshoku Yang, Zi-Jiang Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Junshin Gakuen Univ Dept Med Engn Fac Hlth Sci Fukuoka 8158510 Japan Ibaraki Univ Dept Intelligent Syst Engn Ibaraki 3168511 Japan

ISBN: (纸本)9789881563804

In this paper, a new blind adaptive equalization algorithm under noisy environment is proposed. We consider a practical case where the noise of each transmission channel is unknown. By oversampling the channel output at twice the symbol rate, a single-input double-output channel can be obtained. We apply the recursive-least-squares (RLS) to tackle the blind equalization problem. With the noise-induced bias, RLS algorithm is biased. In order to eliminate the bias, we present a bias-compensated RLS (BCRLS) algorithm that can estimate the unknown additive noise online and the noise-induced bias can be therefore removed. The unbiased estimate of the channel characteristics obtained can be used for channel equalization. Simulations results are presented to demonstrate the performance of the proposed algorithm.

关键词： Blind Equalization recursive least squares algorithm Variance Estimation Bias-compensated Method

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Online Identification and Compensation of the Force Estimating Error in Sensor-less Bilateral Control System

Online Identification and Compensation of the Force Estimati...

引用

15th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Tian, Dapeng Ohnishi, Kouhei Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

ISBN: (纸本)9781424468508

To solve the problem of force estimating error in reaction force observer based sensor-less bilateral control, the online identification and compensation method is proposed based on the recursive least squares algorithm with discontinuous projection mapping. The proposal can identify the system parameters in a fixed bounded range, which guarantees that good performance of the system are not influenced by the compensation. Besides, the force estimating error caused by the parameters mismatch can be canceled. According to experimental results, validity of the proposal is confirmed.

关键词： compensation compensation control system analysis control systems discontinuous projection mapping force control force estimating error least squares approximations online identification reaction force observer recursive estimation recursive least squares algorithm sensor-less bilateral control system torque control

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A Revised Clustering algorithm Based RBF Neural Network Approach for Modeling of an Electro-hydraulic Servo System

A Revised Clustering Algorithm Based RBF Neural Network Appr...

引用

International Conference on Mechatronics and Applied Mechanics (ICMAM 2011)

作者： Chen Jilin Qian Jin Tong Zhongzhi Hou Yuanlong Nanjing Univ Sci & Technol Nanjing 210094 Jiangsu Peoples R China

ISBN: (纸本)9783037853801

The paper presents an approach to model the electro-hydraulic system of a certain explosive mine sweeping device using the Radial Basis Function (RBF) neural network. In order to obtain accurate and simple RBF neural network, a revised clustering method is used to train the hidden node centers of the neural network, in which the subtractive clustering(SC) algorithm was used to determine the initial centers and the fuzzy C - Means(FCM) clustering algorithm to further determined the centers data set. The spread factors and the weights of the neural network are calculated by the modified recursive least squares (MRLS) algorithm for relieving computational burden. The proposed algorithm is verified by its application to the modeling of an electro-hydraulic system, simulation and experiment results clearly indicate the obtained RBF network can model the electro-hydraulic system satisfactorily and comparison results also show that the proposed algorithm performs better than the other methods.

关键词： explosive sweeping mine device clustering algorithm recursive least squares algorithm radial basis function neural network modeling

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Real-time estimation of road friction coefficient for the electric vehicle

Real-time estimation of road friction coefficient for the el...

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3rd World Congress on Software Engineering (WCSE)

作者： Lin Cheng Wang Gang Cao Wan-ke Zhou Feng-jun Beijing Inst Technol Natl Engn Lab Elect Vehicles Beijing 100081 Peoples R China

ISBN: (纸本)9781467345460;9780769548630

The friction coefficient of road is the primary factor of the traction control system. In this paper, a real-time estimation of road coefficient based on the distributed driven electric vehicle is developed. The simplified quarter car model and the Burckhardt tire model are selected and optimized. The algorithm based on recursive least square with forgetting factor is used for road estimation. The test data under a wide range of road conditions are analyzed. The results show that the algorithm is able to estimate two surfaces: asphalt and ice road. The proposed approach has several advantages such as accurate, effective, short cycle and low cost. Also, it has the ability to provide with reliable information for vehicle active safety control.

关键词： electric vehicle distributed driven estimation of road coefficient recursive least squares algorithm

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A Robotic Ball Catcher with Embedded Visual Servo Processor

A Robotic Ball Catcher with Embedded Visual Servo Processor

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Hu, Jwu-Sheng Chien, Ming-Chih Chang, Yung-Jung Chang, Yen-Chung Su, Shyh-Haur Yang, Jwu-Jiun Kai, Chen-Yu Ind Technol Res Inst Mech & Syst Res Labs 195Sec 4Chung Hsing Rd Hsinchu 310 Taiwan Natl Chiao Tung Univ Dept Elect & Control Engn Hsinchu Taiwan Natl Taiwan Univ Sci & Technol Dept Mech Engn Taipei Taiwan

ISBN: (纸本)9781424466757

In this work we present a robotic ball catcher with embedded visual servo processor. The embedded visual servo processor with powerful parallel computing capability is used as the computation platform to track and triangulate a flying ball's position in 3D based on stereo vision. A recursive least squares algorithm for model-based path prediction of the flying ball is used to determine the catch time and position. Experimental results for real time catching of a flying ball are presented by a 6-DOF robot arm. The percentage of success rate of the robotic ball catcher was found to be approximately 60% for the ball thrown to it from five meters away.

关键词： 6-DOF robot arm dexterous manipulators embedded systems embedded visual servo processor manipulator dynamics mobile robots model based path prediction parallel computing path planning recursive least squares algorithm robot vision robotic ball catcher stereo image processing stereo vision visual servoing

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Parameters identification of dual-rate Hammerstein systems based on finite input response models

Parameters identification of dual-rate Hammerstein systems b...

引用

International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE 2012)

作者： Ke, Qin Jing, Chen Wuxi Profess Coll Sci & Technol Wuxi 214028 Peoples R China Jiangnan Univ Sch IoT Engn Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China

ISBN: (纸本)9783037854846

This paper studies the parameter estimation for dual-rate Hammerstein systems. The finite input response model is used to approximate the dual-rate Hammerstein systems, and a recursive least squares algorithm is derived to estimate the parameters of the finite input response model. Based on the estimated parameters, the origin parameters of the dual-rate Hammerstein systems can be obtained. An example is provided to show the effectiveness of the proposed method.

关键词： Parameter estimation FIR model recursive least squares algorithm Hammerstein system

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States and Parameters Estimation for Fractional-order Hammerstein system 17

States and Parameters Estimation for Fractional-order Hammer...

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17th International Multi-Conference on Systems, Signals and Devices (SSD)

作者： Marzougui, Soumaya Atitallah, Asma Bedoui, Saida Abderrahim, Kamel Univ Gabes Natl Sch Engineers Gabes Res Lab Numer Control Ind Proc Gabes Tunisia

ISBN: (纸本)9781728110806

This paper focus on the problem of parameter identification and state estimation for fractional-order Hammerstein system. A new algorithm is developed for identifying simultaneously the model states and parameters. Indeed, we use the recursive least squares method, in order to identify the model parameters, and we extend the Luenberger Observer to estimate the system states. The key is that the estimation of the system parameters uses the estimated states and the estimation of the states uses the estimated parameters. The method efficiency is proved through a simulation example.

关键词： Fractional-order Hammerstein model Parameter Identification State Estimation recursive least squares algorithm Extended Luenberger Observer

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Estimation of parameters in the linear-fractional models

Estimation of parameters in the linear-fractional models

引用

29th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Wu, Fang-Xiang Univ Saskatchewan Dept Mech Engn Saskatoon SK S7N 5A9 Canada

ISBN: (纸本)9781424407873

The linear-fractional model (LFM) is a fraction function whose numerator and denominator are linear in parameters. The LFM is a group of models nonlinear in parameters. The estimation methods for nonlinear models can be applied to the FLM. However, the parameters in an LFM can naturally be divided into two groups: those in the numerator and those in the denominator. When the parameters in the denominator are known, the standard least squares algorithm for the linear model can be used to estimate the parameters in the numerator. On the other hand, when parameters in the numerator are known, by a reciprocal transformation, the standard least squares algorithm for the linear model can again be used to estimate the parameters in the denominator. From this observation, we develop a recursive least-squares algorithm for estimation of parameters in the LFM when both groups has unknown parameters. The basic idea is to estimate the parameters in the numerators for a given initial parameters in the denominator using the standard least squares algorithm for the linear model, and then to estimate the parameters in the denominator with the previous estimates of parameters in the denominator using the standard least squares algorithm for the linear model when new data is available The simulation results validated the convergence of the proposed algorithm and also showed the superior performance of the algorithm proposed over some existing algorithm.

关键词： linear-fractional model (LFM) models nonlinear in parameters parameter estimation recursive least squares algorithm

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External disturbance rejection control based on identification of transfer characteristics from the acceleration sensor for access control of hard disk drive system

External disturbance rejection control based on identificati...

引用

7th International Workshop on Advanced Motion Control

作者： Bando, N Oh, S Hori, Y Univ Tokyo Dept Elect Engn Bunkyo Ku Tokyo 138658 Japan

ISBN: (纸本)0780374797

In this paper, a new method for the external disturbance rejection control which is based on the identification of transfer characteristics from the acccleration sensor is proposed. For hard disk drives, the external disturbance which should be reduced is growing with widespread use of movable computers and other independent machines. In order to reject the effect of the external disturbance we apply the feedforward controller which is designed by recursive least squares (RLS) algorithm and Fixed Trace (FT) algorithm utilizing the acceleration signal and the estimated disturbance signal. Some experimental results in which a disk drive is shaken in the vertical direction are shown to verify the effectiveness of the proposed method.

关键词： hard disk drive accelerometer external disturbance rejection feedforward control recursive least squares algorithm

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